System and method for locating a portable device in different zones relative to a vehicle based upon training data

ABSTRACT

A vehicle system may include a wireless transmitters carried by a vehicle at spaced apart locations and configured to transmit wireless signals, and a portable device moveable relative to the vehicle and configured to receive the wireless signals from the wireless transmitters. A controller may be carried by the vehicle and configured to wirelessly communicate with the portable device, determine a predicted zone the portable device is located in from among a plurality of zones relative to the vehicle based upon the received wireless signals and training data, with the zones having respective vehicle functions associated therewith, and enable the respective vehicle function associated with the predicted zone.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. application Ser. No.16/661,252 filed Oct. 23, 2019, which is a continuation of U.S.application Ser. No. 16/125,049 filed Sep. 7, 2018, which is acontinuation of U.S. application Ser. No. 15/290,120 filed Oct. 10,2016, which in turn claims priority to U.S. provisional application No.62/239,080 filed Oct. 8, 2015, all of which are hereby incorporatedherein in their entireties by reference.

BACKGROUND

In vehicle applications, a smart key allows a driver to keep a key fobpocketed when unlocking, locking and starting a vehicle. For example,the key is identified via one of several antennas in the car's bodyworkand a radio pulse generator in the key's housing. Depending on thesystem, the vehicle is automatically unlocked when a button or sensor onthe door handle or trunk release is pressed.

Vehicles with a smart key system can disengage the immobilizer andactivate the ignition without inserting a key in the ignition, providedthe driver has the key inside the car. On most vehicles, this is done bypressing a starter button.

When leaving a vehicle equipped with a smart key system, the vehicle islocked by either pressing a button on one of the door handles, touchinga capacitive area on a door handle, or by walking away from a vehicle.

Some vehicles automatically adjust settings based on the smart key usedto unlock the car. Such settings may include user preferences such asseat positions, steering wheel position, exterior mirror settings,climate control settings, and stereo presets. Some vehicle models havesettings that can prevent the vehicle from exceeding a maximum speedwhen a certain key is used for starting.

Portable devices, such as smartphones, as well as smartphoneapplications (or programs running on the portable devices), have becomenearly ubiquitous. Smartphone applications have been developed to givesmartphones the functionality of a key fob. For example, a smartphonewith the appropriate software application can be used in place of anelectronic key fob to lock and unlock doors, control a car find feature(e.g., audible horn honk), start a vehicle remotely, or programauxiliary outputs (like trunk release).

Smartphone applications have been developed to receive vehicleinformation via two-way interfaces connected to a vehicle's OBDII port.OBD may stand for On-board diagnostics. Such a smartphone applicationcan be used to ask for reports that score driver habits for aid insafety coaching, conserving fuel and reducing insurance rates, trackvehicle location and help authorities locate the car if it is stolen.Instant alerts can be sent to the smartphone when drivers exceed pre-setgeofence boundaries. In addition, the smartphone application can be usedto request diagnostic reports on vehicle health and preventativemaintenance for tires, brakes, shocks and more.

Smartphone applications may utilize existing communication interfaces inthe smartphone and the vehicle. However, these interfaces may not beconfigured to detect the precise location of the smartphone.

SUMMARY

A vehicle system may include a plurality of wireless transmitterscarried by a vehicle at spaced apart locations and configured totransmit wireless signals, and a portable device moveable relative tothe vehicle and configured to receive the wireless signals from theplurality of wireless transmitters. A controller may be carried by thevehicle and configured to wirelessly communicate with the portabledevice, determine a predicted zone the portable device is located infrom among a plurality of zones relative to the vehicle based upon thereceived wireless signals and training data, the zones having respectivevehicle functions associated therewith, and enable the respectivevehicle function associated with the predicted zone.

In an example embodiment, the training data may be determined based upona machine learning algorithm. By way of example, the machine learningalgorithm may comprise at least one of a neural network, a gradientboosting tree, a naive Bayes classification, a K-nearest neighborclassification, and a support vector machine. Furthermore, the machinelearning may comprise supervised machine learning, for example. Thecontroller may also include a memory storing a previously trainedsupervised machine learning model.

In accordance with an example implementation, the portable device may beconfigured to determine and send respective received signal strengthindicator (RSSI) values to the controller based upon the receivedwireless signals. The controller may also be configured to send thepredicted zone to the portable device. In an example embodiment, thecontroller may be configured to determine the predicted zone locallywithout additional Cloud computing.

In accordance with an example embodiment, one of the zones maycorrespond to a driver side of the vehicle, and the respective vehiclecontrol function for the zone corresponding to the driver side of thevehicle may comprise unlocking at least a driver's door. In anotherexample, one of the zones may correspond to a passenger side of thevehicle, and the respective vehicle control function for the zonecorresponding to the passenger side of the vehicle may compriseunlocking at least a passenger's door. In still another exampleimplementation, a first one of the zones may comprise an away zone, asecond one of the zones may comprise an approach zone within the awayzone, and the controller may be configured to determine whether theportable device is approaching or leaving the vehicle based upon anorder in which the portable device enters the approach and away zones.Moreover, a third one of the zones may comprise a hysteresis zonebetween the away and approach zones, for example.

In yet another example implementation, one of the zones may correspondto a rear of the vehicle, and the respective vehicle function for thezone corresponding to the rear of the vehicle may comprise actuating atleast one of a vehicle trunk and liftgate. In accordance with anotherexample, one of the zones may correspond to a driver's seat within thevehicle, and the respective vehicle function for the zone correspondingto the driver's seat within the vehicle may comprise disabling a textingfunctionality of the portable device. In still another exampleembodiment, one of the zones may correspond to an interior of thevehicle, the vehicle may comprise an infotainment system, and therespective vehicle function for the zone corresponding to the interiorof the vehicle may comprise pairing the portable device with theinfotainment system. In a further example implementation, one of thezones may correspond to an exterior of the vehicle, and the respectivevehicle control function for the zone corresponding to the exterior ofthe vehicle may comprise vehicle door unlocking.

In an example implementation, the wireless transmitters may compriseBluetooth low energy (BLE) beacons. Also by way of example, the portabledevice may comprise at least one of a cellular phone and a key fob.

A related method may include transmitting wireless signals from aplurality of wireless transmitters carried by a vehicle at spaced apartlocations. The method may also include, at a controller carried by thevehicle, wirelessly communicating with a portable device moveablerelative to the vehicle and configured to receive the wireless signalsfrom the plurality of wireless transmitters, determining a predictedzone the portable device is located in from among a plurality of zonesrelative to the vehicle based upon the received wireless signals andtraining data, with the zones having respective vehicle functionsassociated therewith, and enabling the respective vehicle functionassociated with the predicted zone.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of a system according to an exemplaryembodiment of the present invention;

FIG. 2 is a schematic diagram of a Bluetooth passive entry sensor and aBluetooth passive entry module included in the system of FIG. 1according to an exemplary embodiment of the present invention;

FIG. 3 is a schematic diagram illustrating using hysteresis of areceived signal strength indicator (RSSI) signal to prevent vehicledoors from locking and unlocking multiple times as a user approaches athreshold according to an exemplary embodiment of the present invention;and

FIG. 4 is a schematic diagram illustrating locating by checking RSSIagainst all devices in a cycle according to an exemplary embodiment ofthe present invention.

FIG. 5 is a schematic block diagram of a vehicle system in accordancewith an example embodiment providing portable device zone location basedupon training data.

FIG. 6 is a schematic block diagram of the vehicle system of FIG. 5shown in greater detail in accordance with an example implementation.

FIGS. 7-12 are schematic diagrams illustrating the location of aportable device within various zones around a vehicle by the system ofFIG. 6.

FIG. 13 is a flow diagram illustrating example method aspects associatedwith the system of FIG. 6.

DETAILED DESCRIPTION

In accordance with an exemplary embodiment of the preset invention,there is provided a system and method for micro-locating andcommunicating with a portable vehicle control device.

Through use of localization, a portable vehicle control device, such asa smartphone, can have its location approximated or detected relative toa vehicle. This way, if a smartphone is detected inside a vehicle, thesmartphone may be enabled to start the vehicle. In addition, if thesmartphone is detected inside the vehicle and the smartphone is in thedriver's seat, the smartphone's texting feature may be disabled.Further, if the smartphone is detected outside the vehicle near thevehicle's trunk, automatic opening of the trunk/liftgate may befacilitated.

Localization technology enables a smartphone's location to be accuratelydetected under one meter. In one example localization technology, aplurality of Bluetooth low energy (BLE) beacons may be positioned withina vehicle. These beacons are small transmitters whose signals can bedetected by smartphones and tablets. To receive beacon transmissions, asoftware application is installed on the smartphone or tablet. Theapplication uses the transmitted BLE signal to estimate its proximity toa beacon. This enables the delivery of relevant content in the rightphysical space, at the right time.

FIG. 1 illustrates a system according to an exemplary embodiment inwhich BLE localization is used to locate and communicate with a portabledevice. It is to be understood, however, that other localizationtechnologies may be used such as WiFi, Quick Response (QR) codes,Zigbee, Ultra-Wideband (UWB), and ANT (ANT is a proprietary open accessmulticast wireless sensor network technology). It is to be furtherunderstood that BLE localization and UWB can be used with a number ofmobile operating systems including Android and iOS.

Referring now to FIG. 1, there is shown a vehicle control system thatincludes a vehicle 1, a portable device 2 and internet 3.

The portable device 2 may be a smartphone capable of running one or moresmartphone applications, and being carried by a user. The portabledevice 2 may include a control unit and one or more transceivers capableof wireless communication, including, for example, a BLE transceiver anda cellular transceiver. It should be understood that the portable device2 is not limited to a smartphone, and that the portable device 2 may beany type of device carried by a user and separable from a vehicle,including, for example, a tablet or a key fob.

The portable device 2 may communicate with the internet 3 via itscellular transceiver. A variety of mobile telecommunication protocolsmay be employed by the portable device 2. These may include GlobalSystem for Mobile Communications (GSM) and Code Division Multiple Access(CDMA).

The vehicle 1 may include a plurality of BLE proximity sensors 10 a to10 d and a BLE control module 20. The BLE proximity sensors 10 a to 10 dmay be “Bluetooth beacons.” A Bluetooth beacon is a transmitter thatuses BLE to broadcast a signal that can be heard by compatible or smartdevices. These transmitters can be powered by batteries or a fixed powersource such as a Universal Serial Bus (USB) adapter. When a smart deviceis in a beacon's proximity, the beacon will automatically recognize thesmart device and will interact with the smart device.

For example, as shown in FIG. 1, the BLE proximity sensors 10 a to 10 dare capable of transmitting signals to one or more transceivers of theportable device 2. For example, the BLE proximity sensors 10 a to 10 dmay be configured to transmit signals to a BLE transceiver of theportable device 2. As described herein, based on the communicationsignal from the one or more of the BLE proximity sensors 10 a to 10 d,the portable device 2 may determine location information about itself.

The BLE proximity sensors 10 a to 10 d can further communicate with eachother. As an example, they may exchange security data indicating theyare part of the same system and authorized to communicate with othersystem components. In yet another example, they may communicate signalstrength coming from the portable device 2 as well as a time stamp ofthe signal coming from the portable device 2.

The BLE control module 20 may communicate with the BLE proximity sensors10 a to 10 d. This communication may be via a wired or wirelessinterface. For example, the BLE control module 20 and the BLE proximitysensors 10 a to 10 d may communicate over a vehicle bus such as aController Area Network (CAN) bus. The BLE control module 20 maycommunicate with a vehicle control system via the vehicle bus. Forexample, in response to the portable device 2, the BLE control module 20may instruct the vehicle system to lock or unlock a door of the vehicle1.

The BLE control module 20 can communicate with the BLE proximity sensors10 a to 10 d to control behavioral patterns and/or operating modesthereof. As an example, the BLE control module 20 can instruct the BLEproximity sensors 10 a to 10 d to operate, for how long to operate, atwhich frequency to operate, etc. In yet another example, the BLE controlmodule 20 can instruct the BLE proximity sensors 10 a to 10 d when topower up, when to power down or when to run according to a schedule.

The BLE proximity sensors 10 a to 10 d may be disposed at variouslocations on the vehicle 1. Example locations include rearview exteriormirrors, and upper and/or lower portions of the doors, the rear bumperor a combination thereof. As shown in FIG. 1, the BLE control module 20is disposed in the vehicle dash, two BLE proximity sensors 10 a and 10 dare disposed in the rearview exterior mirrors and two BLE proximitysensors 10 b and 10 c are disposed at mid-portions of the passenger anddriver side doors. It should be understood, however, that theembodiments described herein are not limited to this configuration, andthat the BLE control module 20 and the BLE proximity sensors 10 a to 10d may be disposed anywhere in the vehicle 1.

FIG. 2 illustrates a BLE proximity sensor 10 (BT Passive Entry Sensor)and a BLE control module 20 (BT Passive Entry Module) in more detail. Asshown in FIG. 2, the BLE proximity sensor 10 includes a BTsystem-on-chip 11, a voltage regulator 12, antenna array 13 and aconnector 14. The BLE control module 20 includes a microprocessor 21, aBT system-on-chip 22, a voltage regulator 23, antenna array 24, a CANtransceiver 25, a general-purpose input/output (GPIO) 26 and a connector27.

The BT system-on-chip 11 of the BLE proximity sensor 10 enables BLEmaster and slave nodes to be built and includes a radio frequency (RF)transceiver with a software integrated development environment,in-system programmable flash memory and other peripherals to interfacewith a wide range of sensors, etc. The connecter 14 of the BLE proximitysensor 10 may be used to connect the BLE proximity sensor 10 to thevehicle's power supply.

The BT system-on-chip 22 of the BLE control module 20 may operatesimilar to the BT system-on-chip 11 of the BLE proximity sensor 10. Theconnecter 27 of the BLE control module 20 may be used to connect the BLEcontrol module 20 to the vehicle's power supply. The GPIO 26 of the BLEcontrol module 20 may be used to hardwire the BLE control module 20 tothe vehicle's electrical system. The CAN transceiver 25 of the BLEcontrol module 20 allows the microprocessor 21 of the BLE control module20 to communicate with the vehicle's electrical system through a CANbus.

Referring now to FIGS. 1 and 2, in an exemplary embodiment the BLEcontrol module 20 may use its antenna array 24 to communicate with theBLE transceiver of the portable device 2. The antenna array 24 may be adirectional or omnidirectional antenna. The BLE control module 20 mayestablish a BLE connection between itself and the portable device 2,thereby allowing the portable device 2 to communicate with the BLEcontrol module 20 when in proximity to the vehicle 1. Such communicationwill be authorized once the portable device 2 is authenticated by theBLE control module 20.

The BLE proximity sensor 10 c may use its antenna array 13, such as adirectional antenna aimed tower the driver seat, to determine where theportable device 2 is located. For example, if the portable device 2 islocated outside the vehicle 1, the signal strength between BLE proximitysensor 10 c and the portable device 2 may be low. If the portable device2 is located in the rear seat of the vehicle 1, the signal strengthbetween the BLE proximity sensor 10 c and the portable device 2 may below. If the portable device 2 is located in the driver seat, the signalstrength between the BLE proximity sensor 10 c and the portable device 2may be high. Based on the signal strength, the portable device 2 may beable to determine its location, such as whether or not it is in or nearthe driver seat.

For enhanced accuracy, each of the BLE proximity sensors 10 a to 10 dmay transmit a signal to the portable device 2. Based on a combinationof the strength of these signals, the portable device 2 may determineprecise location information about itself. For example, if the signalsreceived from the BLE proximity sensors 10 disposed outside the vehicle1 are weaker than the signals received from the BLE proximity sensors 10disposed outside the vehicle 1, the portable device 2 may know it isinside the vehicle 1. Further, if the signal received from a BLEproximity sensor 10 disposed in the driver side door is stronger thanthe signals received from the BLE proximity sensors 10 disposed in thefront passenger and rear passenger doors, the portable device 2 may knowit is in the driver seat.

Each of the BLE proximity sensors 10 a to 10 d may transmit a Bluetoothdiscovery signal and/or a received signal strength indicator (RSSI)signal to the portable device 2. These signals may be repeatedlytransmitted.

A control unit of the portable device 2 may monitor the signal strength(RSSI data) received from each of the BLE proximity sensors 10 a to 10d. Based on the monitored signal strength, the control unit determinesif the portable device 2 is located in close proximity to the vehicle 1for unlocking or within the front part of the vehicle 1 for starting thevehicle 1. It should be understood that the portable device 2 maydetermine its location in a variety of ways.

For example, the control unit of the portable device 2 may determine thelocation of the portable device 2 based on whether the signal strengthof the BLE proximity sensors 10 a to 10 d exceeds a threshold. Forexample, if the signal strength of the BLE proximity sensor 10 a isabove the threshold, the portable device 2 may know it is near the BLEproximity sensor 10 a. Further, if the signal strength of the BLEproximity sensor 10 b is below the threshold and the signal strength ofthe BLE proximity sensor 10 a is above the threshold, the control unitmay know with more accuracy that the portable device 2 is located nearthe BLE proximity sensor 10 a. The strengths of the signal received fromthe BLE proximity sensors 10 a to 10 d may be sent to the BLE controlmodule 20.

The BLE control module 20 may include a software algorithm stored on itsmemory and operable using its microprocessor 21 to enable the BLEcontrol module 20 to know where the portable device 2 is based onsignals received from the portable device 2. For example, based on thesignal strength of a communication received from the portable device 2,the BLE control module 20 may know if the portable device 2 is insidethe vehicle 1 or outside the vehicle 2. The algorithm may also know thecurrent state of a variety of vehicle features. For example, whether thevehicle's doors are locked or unlocked. In this case, if someone inpossession of the portable device 2 is within a predetermined range ofthe vehicle 1 and this information is provided to the BLE control module20, the currently locked doors may be automatically unlocked. If someonein possession of the portable device 2 is outside another predeterminedrange of the vehicle 1 and this information is provided to the BLEcontrol module 20, the currently unlocked doors may be automaticallylocked. In other words, passive entry features may be accomplished.

It is to be understood that when a door is automatically unlocked, insome cases, the door may be opened without the vehicle owner having tomake physical contact with the door. For example, the door mayseamlessly open as the vehicle owner crosses a predetermined distancethreshold with respect to the vehicle. It is to be further understoodthat the door may not be fully opened, just partially opened, so thatthe door does not touch a vehicle parked nearby.

For example, when a person with the portable device 2 is more than 30feet from the vehicle 1, the vehicle's doors may be locked. When theperson with the portable device 2 is within 10 feet from the vehicle 1,the vehicle's doors may be unlocked. The distances used for locking andunlocking the vehicle's doors may be based on a threshold of signalstrength and may incorporate a time delay.

For example, a radio frequency integrated circuit included in theportable device 2 reports an RSSI that can be used for understandingabsolute power levels of a received transmission (or noise). The RSSIcan be used to approximate a distance between the transmitter and thereceiver with several assumptions such as the transmitter power andantenna gains. The distances assume a certain path loss based ondistance and interference or attenuating factors. A large number ofvariables can change path loss in real time; thus, RSSI is used as arough indicator when one receiver and one transmitter are used. In otherwords, RSSI is used to judge a distance between two devices.

In accordance with an exemplary embodiment hysteresis of the RSSI signalcan be used to prevent the system from locking and unlocking multipletimes as a user approaches a trigger threshold. For example, a singletrigger threshold may be crossed with almost no motion of the user dueto variation in signal strength just above or below the threshold. Toprevent this, the hysteresis may be set with a reasonably large gap sothat once transition from lock to unlock has occurred (as an example), amuch smaller signal threshold may be set to transition again from unlockto lock. The smaller signal may represent a farther distance. Inaddition, a wait time may be set after the first threshold transitionbefore checking the signal again. Further, a wait time may be set afterthe second threshold transition.

For example, as shown in FIG. 3, the system of the vehicle 1 will unlockwhen the user (e.g., portable device 2) approaches and reaches an innerthreshold (e.g., ˜10 ft.). The system will not re-lock unless an outerthreshold (e.g., ˜30 ft.) is exceeded and the user stays past the outerthreshold for a period of time (e.g., 3-5 sec).

In an exemplary embodiment the portable device 2 can have certainfeatures disabled through use of localization. For example, when theportable device 2 is a smartphone, its texting feature can be disabled.For example, when the smartphone is detected through localization asbeing in the driver's seat, the phone's texting feature may be disabled.It is to be understood that other phone features can be disabled. Forexample, videotelephony technologies such as facetime may be disabled.It is to be further understood that phone feature disabling is notlimited to the driver seat and be can adjusted to include phones presentin the front row of a car or anywhere else in a car.

To accomplish this, an app running on the smartphone will communicateRSSI levels between the BLE proximity sensors 10 and calculate itslocation compared to a frame (either a centroid or node). Thisinformation can be compared to established thresholds referenced by theframe to establish zones to allow or disallow mobile device functionssuch as texting.

For example, as shown in FIG. 4, localization can be achieved bychecking RSSI against all devices in a cycle. B1 to B4 represent beaconsin a vehicle and M1 represents a mobile device. Dark lines between thebeacons B1 to B4 represent a beacon frame. A frame is established whenthe beacons B1 to B4 are communicably coupled to each other to form anetwork. In this case, the dark lines between the beacons B1 to B4represent a communication channel between the beacons B1 to B4. Toaccomplish this, the beacons B1 to B4 establish signal strengths betweenneighbors. This way, variations within the frame can be detected.

Using the communicably coupled beacons B1 to B4, a zone Zone can beestablished. The zone Zone is threshold based. For example, the edges ofthe zone Zone can be defined by RSSI values with respect to the beaconsB1 to B4. For example, the lower edge of the zone Zone would have strongRSSI values with B4 and B3, while have weak RSSI values with B1 and B2.The upper edge of the zone Zone would also have strong RSSI values withB4 and B2, but these values would not be as strong as the RSSI values ofthe lower edge of the zone Zone. More than one zone can be created.

When the mobile device M1 is brought into the frame, it can bedetermined whether the mobile device M1 is within the zone Zone. Forexample, signal strength between the mobile device M1 and each of thebeacons B1 to B4 can be measured. The mobile device M1 can then belocated against a centroid of the frame using triangulation techniques.The mobile device's location can then be checked against the boundariesof the zone Zone. If in the zone Zone, the mobile device M1 can bepermitted full functionality (yes text) or limited functionality (notext).

It is to be understood that zones can also be established by estimationusing reference mobile devices at the time of system design and placedinto software as a set of calibrations. Zones can also be established bya training process at the time the mobile device is programmed (paired)to the beacon frame. Training can be a refinement of pre-establishedzones.

In an exemplary embodiment localization may be used to facilitateBluetooth pairing to a vehicle's infotainment system. For example, whena smartphone is in close proximity to an infotainment display in avehicle, the Bluetooth pairing process is initiated between these twodevices. This way, the smartphone can control the infotainment systemwithout having to perform a cumbersome pairing process with the entirevehicle control system. To accomplish this, a zone can be establishednear the vehicle's radio to indicate a function button is to be pressedto accept a pairing request (as an example).

In an exemplary embodiment localization can also be used to determinewhether a person is standing at the back of the vehicle to facilitateautomatic opening of the trunk/liftgate. In this case, a zone would belocated near the rear of the vehicle.

In an exemplary embodiment, a coin cell battery powered back-up walletcard that allows a user to access the vehicle if the smartphone islost/stolen/dead battery can be provided. The wallet card would stillallow the user to unlock and start the vehicle. In this case, the mobiledevice is replaced by a hardware device such as a key fob or wallet cardthat contains a BT radio, micro-controller and firmware that operateslike the app described above.

In an exemplary embodiment Bluetooth tire pressure monitor sensors(TPMS) paired to a vehicle that also add security protection to wheelsmay be provided. For example, if wheels are removed while the securitysystem is armed, then the alarm will be triggered.

For example, the wheel sensors may be configured to act as part of thebeacon frame (the frame does not have to be made by four BT devices). Inthis case, an alert or alarm trigger can be set if one of the beaconsstops functioning or drops out of the network. The beacons may also bedefined by type and alert levels can be set based on type. For example,some types may cause an alarm trigger, while others may not. Further,alerts may be of different forms such as a text message.

In addition, rather than defining the wheel sensors as part of thebeacon frame, the sensors can be defined as additional devices. Forexample, a smartphone may be defined as a first mobile device, adongle/key fob may be defined as a second mobile device and the tiresensors may be defined as a third mobile device. The tire sensors mayinclude their own microprocessor, BT transceiver, power, etc. and theymay be put inside a tire. For example, the tire sensors may be in a lugnut cap or a tire stem.

In an exemplary embodiment all radio frequency (RF) in the car can beBluetooth (BT) instead of Ultra-High Frequency (UHF).

In an exemplary embodiment urban mobility features for zipcar and carsharing services are provided. For example, there may be provided aprocess to share encryption keys to enable car start and unlock based onaccount credentials managed in a cloud database—pay per use or creditcard account, etc. Current systems require a BT connection between thephone and the vehicle. BT connections require the devices be pairedbefore data can flow. In present exemplary embodiment, an app is used toget authorization to pair with the vehicle prior to initiating pair orit will block access. Additionally the pairing process can be simplifiedand be accessible when the vehicle is off and the user is outside thevehicle. In this case, an NFC antenna can be mounted on the inside of awindow surface that will active the BT pairing process and share pairingdata via the Near Field Communication (NFC) channel. In another case,the vehicle can have a telematics module that is in communication withthe cloud service along with the phone. The BT pairing data will flowbetween the vehicle and phone via the internet on a secure channelbrokered by the cloud service.

To enable vehicle access via BT, an exemplary authorization process isas follows:

-   -   1. The service provider preprograms a unique vehicle access key        for each vehicle before end user check out. Each vehicle will        have one or more identifier constant(s): QUID, Bluetooth        Address, and VIN. Each record in the cloud database will include        the aforementioned identifier constants as well as the        preprogrammed vehicle access key. This record data is referred        to as vehicle access information.    -   2. Via mobile app, the end user checks out a vehicle after        payment. The mobile app will access the cloud service to        download and store vehicle access information used for BT link        pairing via SSP (Secure Simple Pairing).    -   3. If a vehicle is unpaired, it will be advertise the vehicle        identifier(s) and wait for connections on a schedule. The mobile        app will attempt pairing when the end user attempts to access        the vehicle.    -   4. If a vehicle is already paired, it will connect to the mobile        device if within BT range.    -   5. Once paired, the end user has full access to the feature set.    -   6. During vehicle check in, the BT link is unpaired and the        vehicle access key is removed from the mobile app. The service        provider then connects to the vehicle in order to create a new        vehicle access key and remove any end user Bluetooth pairing        profiles.

In an exemplary embodiment there is provided a low current BT pingingscheme. For example, polling may be put on a schedule, a ping schedulemay be based on last access to the vehicle, and adaptive scheduling maybe based on location, time of day (e.g., google staking—going to work,coming home from work, shopping). For example, BT beacons advertise on aschedule every 5-10 seconds. The schedule can be made longer or shorter.For example, between 6 am car is frequently used, therefore, up the pingrate.

In an exemplary embodiment there is provided a link to a biometric(e.g., iris recognition, fingerprint, facial/voice recognition, etc.)which adds security for authentication to start a vehicle,authentication to share a vehicle, or login. In this case, through useof biometric identification, only certain people can pair a phone, allowa car to start if a phone battery is dead or a phone won't authenticatefor some reason. Biometric identification can also be used forpersonalized feature controls like memory seat, radio preset, mirrorlocation, teenage restrictions—speed limit, radio volume, geofence zonesettings/alerts, for example. In addition, biometric identification canbe used for True Driver ID for insurance & Customer RelationshipManagement (CRM) services, as well as providing features such astracking and speed alerts—sent through the phone data channel,drowsiness detection and alerts, under-the-influence detection. Forexample, teen driving over 70 mph, text sent to parent's phone.

In an exemplary embodiment eye dilation reaction time is delayed when aperson is under the influence of alcohol. Using internal eyelock systemin rear view mirror, eyelock can do under the influence detection method(e.g., detect rate of eye dilation) using flashing light in mirror tocause pupil to dilate. When rate dilation exceeds an under the influencethreshold, the car may be prevented from being started.

In an exemplary embodiment there is provided a link to an RF—the RFkeypad being used for entry to the vehicle if a phone is dead or lost.In this case, an externally mounted RF keypad can be used to gain entryto the vehicle when a cell phone battery is dead. This allows a user tocharge the phone once in the vehicle to allow car start through cellphone authentication. In addition, access to a car can be permitted andauthenticated using eyelock, fingerprint, or another biometric. Further,a thin wallet card with BT chip and battery can be used. This would beused as a spare key to enable vehicle unlock and start in case of deadcell phone battery. A power switch can be used to enable circuitry onlywhen needed to preserve coin cell life (this feature could extend theuseful life of a back up dongle or wallet card to near 10 years). NFCcan be embedded in the RF keypad to allow for unlock.

In an exemplary embodiment there is provided a link to NFC for initialpairing, using encryption to start and credential sharing. For example,NFC is a secure communication channel that typically requires very lowrange such a 4 cm or less to couple the signal. In the presentembodiment, an NFC antenna can be placed in the vehicle dashboard ornearby and require the phone be placed on the coupling surface to enableit to be used as a secure key. Encryption keys and security data can becommunicated via the NFC channel. Certain credential updates such asdeactivation or ownership transfer can also be limited to occur onlythrough this process. NFC can be used to initiate BT pairing as opposedto advertising and discovery. This can save power.

In an exemplary embodiment a network mesh using the ANT protocol(although other approaches may also be used such as Bluetooth Mesh,etc.) and involving command signal hopping from vehicle to vehicle aswell as data hopping from vehicle to vehicle is provided. In this case,a command signal (lock, remote start, etc.) is tagged with a vehicleaddress and any vehicle with this equipment will receive the signal andrebroadcast to all other nodes in the mesh within range—the signal wouldcontinue to hop until the receiving device finally gets the signal. Thesignal may be prevented from recirculating and may have an expire—theexpire can be a hope count or time limit or both.

In an exemplary embodiment an RF/BLE fob may be yet another peripheralwhich gives a phone access to controlling remote functions (start,locate, security, etc.) by providing a BT or RF gateway to the vehicle's(RSM).

In an exemplary embodiment if you want to borrow a friend's car, a webservice can have a secret key allowing you to borrow the key for twodays, for example. The encryption keys are in the cloud. They are sentto your phone assuming you are a member of the web service. The timepermitted to use the secret key can be extended. Further, when sharingcredentials, functionality can be limited. For example, speed can belimited, trunk access can be denied.

In accordance with an exemplary embodiment by holding phone near radioand turning on BT pairing of the radio, since the phone knows where itis (due to localization), the phone will be paired to the radio.

In accordance with an exemplary embodiment there is provided a safetyfeature to disable the text function on a paired phone when the systemdetermines said phone is in location of the driver seat. For example, ifsame phone is being held by and located in a passenger seat texting isenabled, as soon as it is moved into the driver seat location, textingis disabled. The safety feature can be activated/deactivated when indealer lot mode.

In accordance with an exemplary embodiment, a smart phone can beutilized instead of or in addition to ACM keypad for preload vehiclesecurity access. This eliminates the need for dealers to purchase ACMkeypads and can reduce program costs.

In operation:

-   -   Dealer web browser acts as an administration tool to set up        users/smart phones and view/print usage reports Smart phones are        used at time of install, during sales demos in lot-mode, and to        transition the security product to consumer mode    -   Smart phones control the vehicle security & RKE systems and        transmit the usage activity to the server Smart phone/users are        given access rights by the administrator (time of day and days        of week operation)    -   All usage transactions are sent to the server        -   Vehicle ID        -   Smart phone ID (user)        -   Operation type (lock, unlock, consumer mode transition,            transition type (Red, Green, Yellow, Blue)        -   Timestamp

The use process is as follows:

-   -   User opens smartphone app    -   App checks with server to verify user access and logs in    -   User come within range of vehicle to gain access    -   Possible usage methods to control vehicle        -   Scan VIN barcode, or barcode sticker        -   Hold phone to NFC tag (if system configured and equipped)        -   User presses number sequence keyed to the vehicle 1D        -   Select vehicle from menu list (list populated by all            vehicles within Bluetooth range)

User presses function key

-   -   Lock/unlock/transition

Transaction information is sent via cell network to the sever to createtransaction record

In accordance with an exemplary embodiment the aforementionedlocalization techniques can be used to set up driver preferences likememory seat, radio presets, climate controls, mirror locations, etc.

In accordance with an exemplary embodiment when the phone is detected inthe driver seat area, certain phone features such as Siri and Googlevoice can be automatically engaged.

In accordance with an exemplary embodiment the localization algorithmcan have multiple hysteresis thresholds depending on location and modeof operation. For example, the algorithm can determine instantaneouslocation changes within the beacon frame, but actions and featureactuation can have different hysteresis criteria—these criteria would bebased on reaction to total distance moved into and out of function zonesand also time in and out of the zone as well as rates of movement. Useof the phone's accelerometer may be used in both the feature activationfunctions and in the location algorithm. As an example, the driver maysimply extend their arm (holding phone) to try to defeat the zonetexting lockout. This would happen quickly and for a relatively shortduration. There can also be an activation feature based on location andmotion of the phone such as shake twice to activate Siri if in thedriver zone, etc. Or, shake twice to lock the car when around thevehicle after exiting the car.

Turning now to FIGS. 5-6, another example implementation of a vehiclesystem 30 illustratively includes a plurality of wireless transmitters31 a-31d that are carried by a vehicle 32 at spaced apart locations andare configured to transmit wireless signals. By way of example, thewireless transmitters 31 a-31 d may be BLE transmitters as discussedfurther above and as illustrated in FIG. 6, but here again other typesof wireless communication formats (e.g., UWB, WiFi, Zigbee, etc.) may beused in different embodiments. Furthermore, while there are fourwireless transmitters 31 a-31 d shown in the illustrated example, itwill be appreciated that other numbers of transmitters may be used indifferent embodiments as well.

The system 30 further illustratively includes a portable device 33,which as discussed above may be a cellular phone/smartphone (as shown inFIG. 6), a fob, or other types of portable electronic devices such astablet computers, smart watches, etc. In any event, the portable device33 is moveable relative to the vehicle 32 and is configured to receivethe wireless signals from the wireless transmitters 31 a-31 d, as alsodiscussed above.

A controller 34 is illustratively carried by the vehicle 32 andconfigured to wirelessly communicate with the portable device 33,determine a predicted zone the portable device is located in from amonga plurality of zones relative to the vehicle 32 based upon the receivedwireless signals using the techniques described above, and further basedupon training data. More particularly, each zone has at least onerespective vehicle function associated therewith, and the controller 34is also configured to enable the respective vehicle function associatedwith the predicted zone, as will be discussed further below.

Generally speaking, the system 30 uses training data in the form of atrained model generated from machine learning to make predictions onwhere an end user is (via the end users' portable device 33) about thevehicle 32. This may conceptually be considered as inference-basedlocalization, deriving from the fact that inference is made by a machinelearning algorithm, in which it is predicting where a user is around avehicle (localization) based upon the user's portable device 33.

By way of example, the machine learning algorithm used to derive thetraining data may comprise one or more of a neural network, a gradientboosting tree, a naive Bayes classification, a K-nearest neighborclassification, and a support vector machine. Moreover, the machinelearning may be supervised or unsupervised machine learning. Thecontroller 34 illustratively includes a processor 35 and associatedmemory 36 for storing the previously trained supervised machine learningmodel (FIG. 6). One advantage of using the trained model stored withinthe memory 36 locally at the controller 34 is that this advantageouslyallows the processor 35 to locally make location determinations withoutCloud computing or other remote computing resources. This, in turn, mayresult in quicker location determinations because it avoids latency withrespect to Cloud service communications, and may also avoid the costassociated with a separate wireless (e.g., cellular) service to thevehicle 32. The controller 34 further illustratively includes a wirelesstransceiver 37 (e.g., Bluetooth, etc.) coupled to the processor forwirelessly communicating with the portable device 33.

In the example illustrated in FIG. 6, the portable or mobile device 33will tensor (group together) RSSI values RSSI(A)-RSSI(D) that arereported between itself and all of the BLE transmitters 31 a-31 d at asingle instance, and send these to the controller 34. The controller 34then predicts the location of the end user equipped with the mobiledevice 33 within a given zone around or in the vehicle 32, based off ofthe RSSI values RSSI(A)-RSSI(D) reported to it using the trained model.Once the location is predicted, this prediction is then sent back to themobile device 33, and the process may repeat. In an exampleimplementation, the RSSI values RSSI(A)-RSSI(D) are continuouslyreported between the mobile device 33 and the BLE transmitters 31 a-31d, and an RSSI between the mobile device and the controller 34 is alsoreported. In some embodiments, the controller 34 may be connected to thetransmitters 31 a-31 d at the vehicle (e.g., through a direct wiredconnection, databus, wirelessly, etc.) and selectively control theirtransmissions, such as to disable them when the portable device 33 isaway from the vehicle 32 or enable them as the portable deviceapproaches the vehicle, as will be discussed further below, which may bebeneficial in terms of power savings, for example.

Referring additionally to FIGS. 7-12, example location scenarios by thecontroller 34 will now be discussed. As used herein, a “location” isconsidered a general zone in which the end user (i.e., the portabledevice 33) is present in. It may also be referred to as just a “zone” aswell, and does not have to be interpreted as a numeric measurement(e.g., such as in terms of linear distance or unit of measure), butrather as a prediction of the general location of an end user. In theillustrated example, there are eight zones 70-77 recognized by thecontroller 34, but other numbers of zones may also be used in differentembodiments. The defined zones includes: a driver side zone 70 on thedriver's side of the vehicle 32; a passenger side zone 71 on thepassenger's side of the vehicle; a front zone 72 at a front of thevehicle; a rear zone 73 at a rear/back of the vehicle; an inside zone 74inside of the vehicle; and approach zone 75 surrounding the vehicle; anaway zone 76 surrounding the vehicle and outside of the approach zone;and a hysteresis zone surrounding the vehicle and between the approachand away zones. It should be noted that in some embodiments the interiorzone 74 may correspond to a subset of the vehicle interior (e.g., thedriver's seat area), or be split into interior sub-zones (e.g.,front/rear seats, driver/passenger side seats, etc.), if desired, forenabling different vehicle functions accordingly.

The away zone 76 is defined by whether the portable device 33 (which isa wireless key fob in the illustrated examples) has connected to thecontroller 34 or not, i.e., whether it is in wireless communicationrange. Mobile device 33 (and therefore the user) is in the away zone 76if the mobile device makes a connection with the controller 34 duringapproach. A user is not in the away zone 76 if the mobile device 33 isdisconnected from the controller 34, or it has passed into the next zoneon approach, which in the present case is the hysteresis zone 77. Thereneed not be a “hard-coded” distance threshold associated with the awayzone 76, since the range of connection in different scenarios will bedifferent (e.g., different types of portable devices may have differentranges, etc.). More particularly, the away zone 76 range may be variableand depend on environmental factors such as RF interference, proximityto walls, structures and other vehicles, mobile device placement (e.g.,pocket, bag, etc.). Moreover, the zone location may become moreuncertain with increasing distance from the vehicle 32.

The hysteresis zone 77 allows for a buffer-hysteresis for bridging thetransition between the away zone 76 and the approach zone 75, anddetermining a direction the mobile device 33 is traveling. Moreparticularly, a user is approaching the vehicle (approach threshold) ifhe or she is transitioning from the away zone 76 to the approach zone75, and conversely a user is leaving the vehicle 32 (away threshold) ifhe or she is transitioning from the approach zone to the away zone, asshown in FIG. 7. The hysteresis zone 77 may incrementally bias towardsone direction or the other based on a transition of zones (e.g., a statemachine). This functionality may be used for determining direction ofapproach when desired, or where hard-coded thresholds are usedinternally. In other instances, the hysteresis zone 77 may just betreated as part of the away zone 76.

The approach zone 75 is a zone in which the user may be considered to bewithin a reasonably close distance to the vehicle 32 where the RSSI willcontinue to increase. A user is in the approach zone 75 if he or she haspassed the hysteresis zone 77, or if the user is detected in one of thenear vehicle zones 70-74. A user is not in the approach zone 75 if hehas never connected (i.e., was never in the away zone 76), or has leftthe approach zone 75 transitioning into the away zone after passing theaway threshold. Here again, this functionality may be used fordetermining the direction of approach if desired, or if hard-codedthresholds are used internally. Otherwise, the approach zone could betreated as part of the away zone 76.

The near zones 70-74 are defined by smaller subsets of the approach zone75 and represent different relevant locations around and in the vehicle32. In the example of FIG. 8, the mobile device 33 is within the driverside zone 70, which is indicated by a dotted border (the other nearzones 71-74 have dashed borders to indicate the portable device is notpresent therein), meaning that the user is on the driver's side of thevehicle 32. Vehicle functions that may be associated with the driverside zone may include unlocking the driver door (and optionally otherdoors), such as in response to a handle touch or simply by autounlocking, etc. Other vehicle functions may include triggering approachlights (e.g., head lights) to “greet” a user when transitioning from theaway zone 76 to one of the near zones 70-74, and the converse (i.e.,transitioning from a near zone to the away zone) could trigger anauto-lock timer, for example.

In the example of FIG. 9, the portable device 33 is within the passengerside zone 71, meaning that the user is on the passenger side of thevehicle 32. Example vehicle operations that may be associated with thiszone 71 may include unlocking the passenger door (e.g., automatically orresponsive to a handle touch), etc. In the example of FIG. 10, themobile device 33 is within the rear zone 73 of the vehicle, meaning theuser is at the rear of the vehicle 32. Example vehicle operations thatmay be associated with the rear zone 73 may include actuating a trunk orliftgate (e.g., automatically or responsive to a handle touch/motionsensor), etc. In the example of FIG. 11, the mobile device 33 is withinthe front zone 72, meaning that the user is at the front of the vehicle32. Example vehicle operations that may be associated with the frontzone 72 include releasing a hood latch (e.g., automatically orresponsive to a handle touch/motion sensor), etc. By way of example, anapproximate distance threshold for each of these zones may be in a rangeof 1-2 meters around the vehicle 32, and more particularly around 1.5meters from the skin of the vehicle, although different ranges may beused in different embodiments.

In the example of FIG. 12, the mobile device 33 is in the interior zone74, meaning that the user is inside the vehicle 32. As noted above,example operations that may be associated with the interior zone 74include disabling certain driver mobile device functions (e.g., texting,etc.), pairing the mobile device to an infotainment system, etc. Hereagain, the interior zone 74 may be reduced or sub-divided into a smallerzone(s) for different functions, if desired.

An example approach for determining the location of an end user aboutthe vehicle 32 by the controller 34 is now described. The location maybe determined using the RSSI values of the connection between the mobiledevice 33 and all of the wireless transmitters 31 a-31 d onboard thevehicle 32. More particularly, the location may be determined using thefollowing steps:

-   -   1. Log the RSSI values from each of the wireless transmitters 31        a-31 d by the mobile device 33, all at the same timestamp (or        relatively close).    -   2. Group these values into an ordered array, where the order is        defined currently by the minor value of the sensor (packet) in        the case of a BLE transmitter (other orders may be appropriate        for different wireless formats, as will be appreciated by those        skilled in the art).    -   3. Process and “clean” the data logged on the mobile device 33        (example data cleaning processes for Android and iOS operating        systems will be discussed further below).    -   4. Report the data from the mobile device 33 to the controller        34 at the vehicle 32.    -   5. Run a localization algorithm at the controller 34, using the        ordered array of sensor RSSIs as inputs to the trained model, to        determine location.    -   6. Report the predicted location back to the end user (mobile        device 33).

The following are example approaches that may be used for “cleaning”RSSI data for Android arid iOS operating systems. More particularly, incertain instances the RSSI data may be relatively noisy, in that thereis a lot of meaningless data associated with each log. Generallyspeaking, Android devices do not have an internal operating systemfunctionality to “clean” the data initially like there is on iOScounterparts, which automatically removes outliers, gets better signals,etc. Furthermore, the sampling rate is variable on Android devices, butthis is not the case on iOS devices (it strictly samples every 1second). Furthermore, different types of Android devices have differentBluetooth modules, i.e., there is not a set standard among Androiddevices.

Given the foregoing, to provide a unification of input between bothplatforms, the controller 34 may pre-process the data to put it into auniform format for location determination processing. An exampleapproach to preprocess Android data to unify it with data that emanatesfrom an iOS platform is detailed below.

-   -   1. Use a sampling interval of 100 ms (0.1 s), and take 10        samples of all N onboard sensors forming a column array.    -   2. If any column input>MAX_RSSI, then set it to MAX_RSSI.    -   3. If any column input<MIN_RSSI, then set it to MIN_RSSI.    -   4. Take the average of each column matrix, excluding any dropped        signals from the averaging.    -   5. If column average:=DROPPED_SIG, then set it to MAX_RSSI.    -   6. Take the averaged (cleaned) input of each column and form an        input array to the localization algorithm.

Unlike Android, iOS devices may provide a more stable platform forlogging RSSI, such that not much pre-processing needs to be done since,in the present example, it is intended that the Android data is to bemade to look like the iOS data. Some features that iOS devices providethat are useful for this purpose include: unity across generations ofdevices, as newer/older iPhones generally operate with the similarchipsets and internal functionality on Bluetooth data; and internal andinherent RSSI processing that reports clean, imputed (removed ofoutliers) RSSI logs with relatively little noise. With respect to iOSlogged data, the following may be performed:

-   -   1. For every i:=0 to NUM_SENSORS.        -   a. If RSSI_LOG[i]>MAX_RSSI, then RSSI_LOG[i]:=MAX_RSSI        -   b. If RSSI_LOG[i]<MIN_RSSI, then RSSI_LOG[i]:=MIN_RSSI        -   c. If RSSI_LOG[i]==DROPPED_SIG, then RSSI_LOG[i]=MAX_RSSI

Further details regarding machine learning approaches for generatingmodel training data are now provided. At a high level the model performsthe following functions: determine the true weights and biases betweenall nodes (i.e., wireless transmitters 31 a-31 d) in the network, andinternally model how they operate with respect to each other; create amathematical model based on these inputs, weights and biases that willfit its curve as close to optimally as possible, and allow room foroutlier data to be mapped to its true output with precision andaccuracy; and use its learning ability to make the use of hard-codedthresholds in core-localization obsolete.

In a neural network approach, the neural network is a machine learningmathematical abstraction that is modeled loosely after the human brain.It includes elements that can be mathematically abstracted thataccurately represent how a human brain makes decisions, makesassociations, etc. A node is the fundamental, atomic unit of a neuralnetwork. Mathematically speaking, it can be seen as just a function orcomputation. It combines the input from the user (or from a previousnode) with a set of coefficients (i.e., weights) that either amplify ordampen the input, similar to a brain neuron in which certain inputs aremore significant for a situation than others. These products are summedup and passed through the node's activation function to determine towhat extent that node will be activated, if at all. If a signal passesthrough the node, this is known as the node firing.

The mathematical abstraction of a node previously described, in which itrepresents that of a neuron of a human brain, is widely used in atypical neural network. The nodes that are firing may send their outputsto even more nodes, a concept known as deep learning. A layer in aneural network is a set of N nodes that will either turn on (firing) oroff (not firing). In mathematical terms, a neural network can usually bereferred to as a dense graph, meaning that all the nodes from somearbitrary layer will connect to all the nodes in the next sequentiallayer. This means that each node in any layer will have input data fromall the nodes from the previous layer. The goal of deep learning is tohave certain inputs/outputs of layers create unique numerical (node)patterns which may be interpreted as a motivated output.

To generate a neural network model that accurately predicts a desiredclassification scheme, it is trained for the input it is supposed totake. This process in particular is called supervised learning, sinceyou follow two basic steps in the process:

-   -   1. Feed the model with N input values (the number of sensors of        input, a.k.a the number of nodes in the input layer); and    -   2. Inform the model that these inputs will map to a specific        output (one of the output nodes).

For a neural network to learn, it should be able to determine how“wrong” it was during the training step. This is done with twomathematical concepts: a loss function and an optimizer for that lossfunction. A loss function in its simplest form is comparable to a costfunction in economics. After a training epoch (iteration), to make themodel better, the model validates the training data against itself, thusmaking predictions of data it has seen before. The loss function willthen calculate the difference between what was predicted, and what theactual output should have been, which is used by the optimizer. Theoptimizer is simply a way to evaluate the loss of a single iteration,and back-propagates through the neural net to adjust the weights andbiases between the edges.

To visualize this, one may think of the loss of a training epoch as acurve. The optimizer's job is to minimize the curve by tweaking theweights and biases and running again. This is commonly done using thepartial derivative ∇, in other terms, the gradient of the loss function.Once this is taken, it moves the weights and biases in the oppositedirection of the gradient, then runs again until it is close to optimal.

In an example neural networks approach, training data is fed through aframework over the course of a training session (e.g., 5 minutes,although other time periods may also be used) to model interiorparameters. Then a test data set may be run through the model to testits accuracy, and an additional training session(s) may be performed iffurther model accuracy is desired. The model may then be converted to abinary file that is uploaded into the embedded system of the controller34, which may then input the reported RSSI data to the model to predictthe location of the mobile device 33. Not only does this approach allowfor localization determinations by the controller 34 without the needfor any external processing, it avoids the need to load extraneous dataused for the testing/training to the controller 34, as the controllermay perform its localization processing based upon just the uploadedmodel binary file, as will be appreciated by those skilled in the art.The following are further details on a neural networks approach whichmay be used in an example implementation:

-   -   1. Create an input layer that has as many nodes as there are        inputs:        -   a. In an example embodiment, there are seven different            wireless transmitters reporting, so, there will be an input            layer of 7.    -   2. Create an arbitrary amount of hidden layers:        -   a. A hidden layer is a layer that allows the neural network            to form more complex patterns;        -   b. More neurons are firing/not firing from inputs of the            previous layer(s), allowing for more granular, and complex            patterns to form;        -   c. A hidden layer possess the activation functions that were            discussed prior, these will determine how to allow nodes to            fire;        -   d. More layers cost more time and memory.    -   3. Create an output layer that has as many nodes as there are        possible outputs or states:        -   a. For the present embodiment, there are six different            zones, so there will be an output layer of 6;        -   b. The output layer will output scores of each class, the            highest score will be the predicted index (node).    -   4. Compile the model with learning parameters:        -   a. These include optimizations for the cost function (loss)            and the optimizer described previously.    -   5. Feed the model inputs as an array of the size of the # of        input nodes, and an output (class) will be predicted.

In accordance with one example implementation, a localization algorithmrunning on the controller 34 uses a neural network machine model to makepredictions regarding the zone in which the user is currently located.The neural network model is actually running onboard the vehicle at thecontroller 34. That is, no cloud computing component is involved for themachine learning operations and processing. The following is an exampleneural network specification which may be used, although otherapproaches/settings may be used in different embodiments:

-   -   Neural network backend—TensorFlow Lite by Google    -   Number of inputs—seven (7)    -   Number of outputs—six (6), returns probability scores    -   Hidden layers . . .        -   H1—128 nodes, rectified-linear unit activation        -   H2—128 nodes, rectified-linear unit activation    -   Loss & optimization . . .        -   Loss—sparse categorical cross entropy        -   Optimizer—ADAM optimizer

The following is example embedded neural network specification:

-   -   Core—TensorFlow Lite (from TensorFlow model) ported to C wrapper    -   Binary size—roughly 75 kB

The above-described approach advantageously capitalizes on robustmachine learning algorithms as its core inference (prediction) maker onexterior zones about an object (vehicle), removing the need forhard-coded thresholds and filters for different scenarios as othermethods have used in prior systems. One advantageous characteristicabout this approach is that it allows for predictions usingresource-constrained embedded systems (i.e., machine learning has astigma of only being capable of running efficiently onresource-plentiful computers, clouds, etc., but the present approachallows for local processing).

Furthermore, the above-described approach may advantageously avoidangles or distances like other localization methods using machinelearning require. For example, existing locating approaches using BLE,UWB, etc. with machine learning typically use some form of distanceregression output from machine learning algorithms. Still anotheradvantage is that this approach makes predictions on exterior zones orlocations, whereas other prior approaches typically use some form ofindoor triangulation via machine learning with similar sensors todetermine location.

It should be noted that the above-described approaches may be used onmore than just automobiles in some implementations. For example, onesuch implementation may include using sensors around the exterior wallsof a building and creating custom zones of location.

A related method is now described with reference to the flow diagram 130of FIG. 13. Beginning at Block 131, the method illustratively includestransmitting wireless signals from a plurality of wireless transmitters31 a-31 d carried by a vehicle 32 at spaced apart locations, at Block132. The method also illustratively includes, at a controller 34 carriedby the vehicle 32, wirelessly communicating with a portable device 33moveable relative to the vehicle and configured to receive the wirelesssignals from the plurality of wireless transmitters 31 a-31 d, at Block133. The method further illustratively includes determining a predictedzone the portable device 33 is located in from among a plurality ofzones 70-77 relative to the vehicle 32 based upon the received wirelesssignals and training data (e.g. a trained model) (Block 134), with thezones having respective vehicle functions associated therewith, andenabling the respective vehicle function associated with the predictedzone (Block 135), as discussed further above. The method of FIG. 13illustratively concludes at Block 136.

Many modifications and other embodiments will come to the mind of oneskilled in the art having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it isunderstood that the foregoing is not to be limited to the exampleembodiments, and that modifications and other embodiments are intendedto be included within the scope of the appended claims.

That which is claimed is:
 1. A vehicle system comprising: a plurality ofwireless transmitters carried by a vehicle at spaced apart locations andconfigured to transmit wireless signals; a portable device moveablerelative to the vehicle and configured to receive the wireless signalsfrom the plurality of wireless transmitters; and a controller carried bythe vehicle and configured to wirelessly communicate with the portabledevice, determine a predicted zone the portable device is located infrom among a plurality of zones relative and adjacent to the vehiclebased upon the received wireless signals and training data, the zoneshaving respective vehicle functions associated therewith, and enable therespective vehicle function associated with the predicted zone.
 2. Thevehicle system of claim 1 wherein the training data is determined basedupon a machine learning algorithm.
 3. The vehicle system of claim 2wherein the machine learning algorithm comprises at least one of aneural network, a gradient boosting tree, a naïve Bayes classification,a K-nearest neighbor classification, and a support vector machine. 4.The vehicle system of claim 2 wherein the machine learning comprisessupervised machine learning.
 5. The vehicle system of claim 1 whereinthe controller comprises a memory storing a previously trainedsupervised machine learning model.
 6. The vehicle system of claim 1wherein the portable device is configured to determine and sendrespective received signal strength indicator (RSSI) values to thecontroller based upon the received wireless signals.
 7. The vehiclesystem of claim 1 wherein the controller is configured to send thepredicted zone to the portable device.
 8. The vehicle system of claim 1wherein the controller is configured to determine the predicted zonelocally without additional Cloud computing.
 9. The vehicle system ofclaim 1 wherein one of the zones corresponds to a driver side of thevehicle; and wherein the respective vehicle control function for thezone corresponding to the driver side of the vehicle comprises unlockingat least a driver's door.
 10. The vehicle system of claim 1 wherein oneof the zones corresponds to a passenger side of the vehicle; and whereinthe respective vehicle control function for the zone corresponding tothe passenger side of the vehicle comprises unlocking at least apassenger's door.
 11. The vehicle system of claim 1 wherein a first oneof the zones comprises an away zone, and a second one of the zonescomprises an approach zone within the away zone; and wherein thecontroller is configured to determine whether the portable device isapproaching or leaving the vehicle based upon an order in which theportable device enters the approach and away zones.
 12. The vehiclesystem of claim 11 wherein a third one of the zones comprises ahysteresis zone between the away and approach zones.
 13. The vehiclesystem of claim 1 wherein one of the zones corresponds to a rear of thevehicle; and wherein the respective vehicle function for the zonecorresponding to the rear of the vehicle comprises actuating at leastone of a vehicle trunk and liftgate.
 14. The vehicle system of claim 1wherein one of the zones corresponds to a driver's seat within thevehicle; and wherein the respective vehicle function for the zonecorresponding to the driver's seat within the vehicle comprisesdisabling a texting functionality of the portable device.
 15. Thevehicle system of claim 1 wherein one of the zones corresponds to aninterior of the vehicle; wherein the vehicle comprises an infotainmentsystem; and wherein the respective vehicle function for the zonecorresponding to the interior of the vehicle comprises pairing theportable device with the infotainment system.
 16. The vehicle system ofclaim 1 wherein one of the zones corresponds to an exterior of thevehicle; and wherein the respective vehicle control function for thezone corresponding to the exterior of the vehicle comprises vehicle doorunlocking.
 17. The vehicle system of claim 1 wherein the wirelesstransmitters comprise Bluetooth low energy (BLE) beacons.
 18. Thevehicle system of claim 1 wherein the portable device comprises at leastone of a cellular phone and a key fob.
 19. A vehicle system comprising:a plurality of wireless transmitters carried by a vehicle at spacedapart locations and configured to transmit wireless signals; and acontroller carried by the vehicle and configured to wirelesslycommunicate with a portable device moveable relative to the vehicle andconfigured to receive the wireless signals from the plurality ofwireless transmitters, determine a predicted zone the portable device islocated in from among a plurality of zones relative and adjacent to thevehicle based upon the received wireless signals and training data, thezones having respective vehicle functions associated therewith, andenable the respective vehicle function associated with the predictedzone.
 20. The vehicle system of claim 19 wherein the training data isdetermined based upon a machine learning algorithm.
 21. The vehiclesystem of claim 19 wherein the controller comprises a memory storing apreviously trained supervised machine learning model.
 22. The vehiclesystem of claim 19 wherein the controller is configured to send thepredicted zone to the portable device.
 23. The vehicle system of claim19 wherein one of the zones corresponds to a driver side of the vehicle;and wherein the respective vehicle control function for the zonecorresponding to the driver side of the vehicle comprises unlocking atleast a driver's door.
 24. The vehicle system of claim 19 wherein one ofthe zones corresponds to a passenger side of the vehicle; and whereinthe respective vehicle control function for the zone corresponding tothe passenger side of the vehicle comprises unlocking at least apassenger's door.
 25. The vehicle system of claim 19 wherein a first oneof the zones comprises an away zone, and a second one of the zonescomprises an approach zone within the away zone; and wherein thecontroller is configured to determine whether the portable device isapproaching or leaving the vehicle based upon an order in which theportable device enters the approach and away zones.
 26. The vehiclesystem of claim 19 wherein one of the zones corresponds to a rear of thevehicle; and wherein the respective vehicle function for the zonecorresponding to the rear of the vehicle comprises actuating at leastone of a vehicle trunk and liftgate.
 27. The vehicle system of claim 19wherein one of the zones corresponds to a driver's seat within thevehicle; and wherein the respective vehicle function for the zonecorresponding to the driver's seat within the vehicle comprisesdisabling a texting functionality of the portable device.
 28. Thevehicle system of claim 19 wherein one of the zones corresponds to aninterior of the vehicle; wherein the vehicle comprises an infotainmentsystem; and wherein the respective vehicle function for the zonecorresponding to the interior of the vehicle comprises pairing theportable device with the infotainment system.
 29. The vehicle system ofclaim 19 wherein the wireless transmitters comprise Bluetooth low energy(BLE) beacons; and wherein the portable device comprises at least one ofa cellular phone and a key fob.
 30. A method comprising: transmittingwireless signals from a plurality of wireless transmitters carried by avehicle at spaced apart locations; and at a controller carried by thevehicle, wirelessly communicating with a portable device moveablerelative to the vehicle and configured to receive the wireless signalsfrom the plurality of wireless transmitters, determining a predictedzone the portable device is located in from among a plurality of zonesrelative and adjacent to the vehicle based upon the received wirelesssignals and training data, the zones having respective vehicle functionsassociated therewith, and enabling the respective vehicle functionassociated with the predicted zone.
 31. The method of claim 30 whereinthe training data is determined based upon a machine learning algorithm.32. The method of claim 30 further comprising sending the predicted zonefrom the controller to the portable device.
 33. The method of claim 30wherein one of the zones corresponds to a driver side of the vehicle;and wherein the respective vehicle control function for the zonecorresponding to the driver side of the vehicle comprises unlocking atleast a driver's door.
 34. The method of claim 30 wherein a first one ofthe zones comprises an away zone, and a second one of the zonescomprises an approach zone within the away zone; and further comprisingdetermining at the controller whether the portable device is approachingor leaving the vehicle based upon an order in which the portable deviceenters the approach and away zones.
 35. The method of claim 30 whereinone of the zones corresponds to a rear of the vehicle; and wherein therespective vehicle function for the zone corresponding to the rear ofthe vehicle comprises actuating at least one of a vehicle trunk andliftgate.
 36. The method of claim 30 wherein one of the zonescorresponds to a driver's seat within the vehicle; and wherein therespective vehicle function for the zone corresponding to the driver'sseat within the vehicle comprises disabling a texting functionality ofthe portable device.
 37. The method of claim 30 wherein one of the zonescorresponds to an interior of the vehicle; wherein the vehicle comprisesan infotainment system; and wherein the respective vehicle function forthe zone corresponding to the interior of the vehicle comprises pairingthe portable device with the infotainment system.